
from __future__ import annotations

import unittest

import numpy as np

from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
				import tensorflow as tf

				from transformers.models.layoutlm.modeling_tf_layoutlm import (
				    TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFLayoutLMForMaskedLM,
				    TFLayoutLMForQuestionAnswering,
				    TFLayoutLMForSequenceClassification,
				    TFLayoutLMForTokenClassification,
				    TFLayoutLMModel,
				)







class 				UpperCAmelCase						:

					def __init__(      self   :       int			,   lowerCAmelCase   :       Union[str, Any]			,   lowerCAmelCase   :       List[Any]=13			,   lowerCAmelCase   :       Tuple=7			,   lowerCAmelCase   :       List[str]=True			,   lowerCAmelCase   :       Optional[Any]=True			,   lowerCAmelCase   :       int=True			,   lowerCAmelCase   :       Union[str, Any]=True			,   lowerCAmelCase   :       Optional[int]=99			,   lowerCAmelCase   :       int=32			,   lowerCAmelCase   :       str=2			,   lowerCAmelCase   :       str=4			,   lowerCAmelCase   :       Optional[int]=37			,   lowerCAmelCase   :       Any="gelu"			,   lowerCAmelCase   :       List[str]=0.1			,   lowerCAmelCase   :       List[str]=0.1			,   lowerCAmelCase   :       Optional[int]=512			,   lowerCAmelCase   :       int=16			,   lowerCAmelCase   :       Union[str, Any]=2			,   lowerCAmelCase   :       List[str]=0.02			,   lowerCAmelCase   :       int=3			,   lowerCAmelCase   :       str=4			,   lowerCAmelCase   :       Dict=None			,   lowerCAmelCase   :       Any=1000			,   ):
											lowercase							:     str									=	parent
											lowercase							:     Union[str, Any]									=	batch_size
											lowercase							:     str									=	seq_length
											lowercase							:     Dict									=	is_training
											lowercase							:     List[Any]									=	use_input_mask
											lowercase							:     List[Any]									=	use_token_type_ids
											lowercase							:     Optional[Any]									=	use_labels
											lowercase							:     Tuple									=	vocab_size
											lowercase							:     int									=	hidden_size
											lowercase							:     Tuple									=	num_hidden_layers
											lowercase							:     Optional[Any]									=	num_attention_heads
											lowercase							:     Dict									=	intermediate_size
											lowercase							:     Optional[int]									=	hidden_act
											lowercase							:     List[str]									=	hidden_dropout_prob
											lowercase							:     Any									=	attention_probs_dropout_prob
											lowercase							:     Union[str, Any]									=	max_position_embeddings
											lowercase							:     List[str]									=	type_vocab_size
											lowercase							:     Dict									=	type_sequence_label_size
											lowercase							:     Dict									=	initializer_range
											lowercase							:     Union[str, Any]									=	num_labels
											lowercase							:     List[Any]									=	num_choices
											lowercase							:     Tuple									=	scope
											lowercase							:     List[Any]									=	range_bbox

					def 							_lowerCAmelCase						(      self   :       List[Any]       ):
											lowercase							:     Union[str, Any]									=	ids_tensor([self.batch_size, self.seq_length]			,   self.vocab_size       )

											# convert bbox to numpy since TF does not support item assignment
											lowercase							:     int									=	ids_tensor([self.batch_size, self.seq_length, 4]			,   self.range_bbox       ).numpy()
											# Ensure that bbox is legal
											for i in range(bbox.shape[0]       ):
																	for j in range(bbox.shape[1]       ):
																							if bbox[i, j, 3] < bbox[i, j, 1]:
																													lowercase							:     Union[str, Any]									=	bbox[i, j, 3]
																													lowercase							:     List[str]									=	bbox[i, j, 1]
																													lowercase							:     int									=	t
																							if bbox[i, j, 2] < bbox[i, j, 0]:
																													lowercase							:     List[str]									=	bbox[i, j, 2]
																													lowercase							:     Optional[Any]									=	bbox[i, j, 0]
																													lowercase							:     List[str]									=	t
											lowercase							:     Dict									=	tf.convert_to_tensor(SCREAMING_SNAKE_CASE_       )

											lowercase							:     Union[str, Any]									=	None
											if self.use_input_mask:
																	lowercase							:     Optional[int]									=	random_attention_mask([self.batch_size, self.seq_length]       )

											lowercase							:     Optional[int]									=	None
											if self.use_token_type_ids:
																	lowercase							:     Dict									=	ids_tensor([self.batch_size, self.seq_length]			,   self.type_vocab_size       )

											lowercase							:     List[Any]									=	None
											lowercase							:     Any									=	None
											lowercase							:     str									=	None
											if self.use_labels:
																	lowercase							:     int									=	ids_tensor([self.batch_size]			,   self.type_sequence_label_size       )
																	lowercase							:     str									=	ids_tensor([self.batch_size, self.seq_length]			,   self.num_labels       )
																	lowercase							:     str									=	ids_tensor([self.batch_size]			,   self.num_choices       )

											lowercase							:     int									=	LayoutLMConfig(
											    vocab_size=self.vocab_size			,   hidden_size=self.hidden_size			,   num_hidden_layers=self.num_hidden_layers			,   num_attention_heads=self.num_attention_heads			,   intermediate_size=self.intermediate_size			,   hidden_act=self.hidden_act			,   hidden_dropout_prob=self.hidden_dropout_prob			,   attention_probs_dropout_prob=self.attention_probs_dropout_prob			,   max_position_embeddings=self.max_position_embeddings			,   type_vocab_size=self.type_vocab_size			,   initializer_range=self.initializer_range			,   )

											return config, input_ids, bbox, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels

					def 							_lowerCAmelCase						(      self   :       Union[str, Any]			,   lowerCAmelCase   :       List[str]			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       Any			,   lowerCAmelCase   :       List[Any]			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       Any			,   lowerCAmelCase   :       List[str]       ):
											lowercase							:     Optional[int]									=	TFLayoutLMModel(config=SCREAMING_SNAKE_CASE_       )

											lowercase							:     Optional[Any]									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_       )
											lowercase							:     Optional[int]									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_       )
											lowercase							:     int									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_       )
											self.parent.assertEqual(result.last_hidden_state.shape			,   (self.batch_size, self.seq_length, self.hidden_size)       )
											self.parent.assertEqual(result.pooler_output.shape			,   (self.batch_size, self.hidden_size)       )

					def 							_lowerCAmelCase						(      self   :       str			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       Any			,   lowerCAmelCase   :       List[str]			,   lowerCAmelCase   :       Union[str, Any]			,   lowerCAmelCase   :       Optional[int]			,   lowerCAmelCase   :       Optional[int]			,   lowerCAmelCase   :       List[Any]			,   lowerCAmelCase   :       Any       ):
											lowercase							:     List[str]									=	TFLayoutLMForMaskedLM(config=SCREAMING_SNAKE_CASE_       )

											lowercase							:     Optional[int]									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_			,   labels=SCREAMING_SNAKE_CASE_       )
											self.parent.assertEqual(result.logits.shape			,   (self.batch_size, self.seq_length, self.vocab_size)       )

					def 							_lowerCAmelCase						(      self   :       str			,   lowerCAmelCase   :       str			,   lowerCAmelCase   :       Any			,   lowerCAmelCase   :       Dict			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       List[str]			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       Optional[int]			,   lowerCAmelCase   :       Dict       ):
											lowercase							:     str									=	self.num_labels
											lowercase							:     Tuple									=	TFLayoutLMForSequenceClassification(config=SCREAMING_SNAKE_CASE_       )

											lowercase							:     Optional[int]									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_       )
											self.parent.assertEqual(result.logits.shape			,   (self.batch_size, self.num_labels)       )

					def 							_lowerCAmelCase						(      self   :       Union[str, Any]			,   lowerCAmelCase   :       List[str]			,   lowerCAmelCase   :       int			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       Any			,   lowerCAmelCase   :       List[Any]			,   lowerCAmelCase   :       Optional[Any]			,   lowerCAmelCase   :       str			,   lowerCAmelCase   :       int       ):
											lowercase							:     int									=	self.num_labels
											lowercase							:     str									=	TFLayoutLMForTokenClassification(config=SCREAMING_SNAKE_CASE_       )

											lowercase							:     Optional[Any]									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_			,   labels=SCREAMING_SNAKE_CASE_       )
											self.parent.assertEqual(result.logits.shape			,   (self.batch_size, self.seq_length, self.num_labels)       )

					def 							_lowerCAmelCase						(      self   :       Union[str, Any]			,   lowerCAmelCase   :       Tuple			,   lowerCAmelCase   :       str			,   lowerCAmelCase   :       Optional[Any]			,   lowerCAmelCase   :       List[Any]			,   lowerCAmelCase   :       List[Any]			,   lowerCAmelCase   :       Optional[Any]			,   lowerCAmelCase   :       Any			,   lowerCAmelCase   :       Dict       ):
											lowercase							:     List[Any]									=	TFLayoutLMForQuestionAnswering(config=SCREAMING_SNAKE_CASE_       )

											lowercase							:     Union[str, Any]									=	model(SCREAMING_SNAKE_CASE_			,   SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_       )
											self.parent.assertEqual(result.start_logits.shape			,   (self.batch_size, self.seq_length)       )
											self.parent.assertEqual(result.end_logits.shape			,   (self.batch_size, self.seq_length)       )




					def 							_lowerCAmelCase						(      self   :       Union[str, Any]       ):
											lowercase							:     List[Any]									=	self.prepare_config_and_inputs()
											(
											    lowercase							
											)							:     Union[str, Any]									=	config_and_inputs
											lowercase							:     str									=	{
											    """input_ids""": input_ids,
											    """bbox""": bbox,
											    """token_type_ids""": token_type_ids,
											    """attention_mask""": input_mask,
											}
											return config, inputs_dict







@require_tf
class 				UpperCAmelCase						( _lowerCAmelCase    ,			_lowerCAmelCase    ,			unittest.TestCase       ):
					a__:			List[Any]      	=					(
					    (
					        TFLayoutLMModel,
					        TFLayoutLMForMaskedLM,
					        TFLayoutLMForTokenClassification,
					        TFLayoutLMForSequenceClassification,
					        TFLayoutLMForQuestionAnswering,
					    )
					    if is_tf_available()
					    else ()
					)
					a__:			Optional[Any]      	=					(
					    {
					        """feature-extraction""": TFLayoutLMModel,
					        """fill-mask""": TFLayoutLMForMaskedLM,
					        """text-classification""": TFLayoutLMForSequenceClassification,
					        """token-classification""": TFLayoutLMForTokenClassification,
					        """zero-shot""": TFLayoutLMForSequenceClassification,
					    }
					    if is_tf_available()
					    else {}
					)
					a__:			Optional[int]      	=					False
					a__:			Dict      	=					True
					a__:			List[Any]      	=					10

					def 							_lowerCAmelCase						(      self   :       Optional[int]       ):
											lowercase							:     str									=	TFLayoutLMModelTester(self       )
											lowercase							:     int									=	ConfigTester(self			,   config_class=SCREAMING_SNAKE_CASE_			,   hidden_size=37       )

					def 							_lowerCAmelCase						(      self   :       str       ):
											self.config_tester.run_common_tests()

					def 							_lowerCAmelCase						(      self   :       str       ):
											lowercase							:     Optional[int]									=	self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_model(*SCREAMING_SNAKE_CASE_       )

					def 							_lowerCAmelCase						(      self   :       Optional[Any]       ):
											lowercase							:     Optional[Any]									=	self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_for_masked_lm(*SCREAMING_SNAKE_CASE_       )

					def 							_lowerCAmelCase						(      self   :       List[Any]       ):
											lowercase							:     Dict									=	self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_for_sequence_classification(*SCREAMING_SNAKE_CASE_       )

					def 							_lowerCAmelCase						(      self   :       Tuple       ):
											lowercase							:     Dict									=	self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_for_token_classification(*SCREAMING_SNAKE_CASE_       )

					def 							_lowerCAmelCase						(      self   :       List[Any]       ):
											lowercase							:     str									=	self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_for_question_answering(*SCREAMING_SNAKE_CASE_       )

					@slow
					def 							_lowerCAmelCase						(      self   :       Any       ):
											for model_name in TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
																	lowercase							:     str									=	TFLayoutLMModel.from_pretrained(SCREAMING_SNAKE_CASE_       )
																	self.assertIsNotNone(SCREAMING_SNAKE_CASE_       )




					@unittest.skip('''Onnx compliancy broke with TF 2.10'''       )
					def 							_lowerCAmelCase						(      self   :       Dict       ):
											pass





def 							lowerCamelCase_   (      ):
						lowercase							:     Union[str, Any]									=	tf.convert_to_tensor([[1_01,10_19,10_14,10_16,10_37,1_28_49,47_47,10_04,1_42_46,22_78,54_39,45_24,50_02,29_30,21_93,29_30,43_41,32_08,10_05,10_55,21_71,28_48,1_13_00,35_31,1_02],[1_01,40_70,40_34,70_20,10_24,30_58,10_15,10_13,28_61,10_13,60_70,1_92_74,27_72,62_05,2_78_14,1_61_47,1_61_47,43_43,20_47,1_02_83,1_09_69,1_43_89,10_12,23_38,1_02]]							)  # noqa: E231
						lowercase							:     int									=	tf.convert_to_tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],]							)  # noqa: E231
						lowercase							:     Optional[Any]									=	tf.convert_to_tensor([[[0,0,0,0],[4_23,2_37,4_40,2_51],[4_27,2_72,4_41,2_87],[4_19,1_15,4_37,1_29],[9_61,8_85,9_92,9_12],[2_56,38,3_30,58],[2_56,38,3_30,58],[3_36,42,3_53,57],[3_60,39,4_01,56],[3_60,39,4_01,56],[4_11,39,4_71,59],[4_79,41,5_28,59],[5_33,39,6_30,60],[67,1_13,1_34,1_31],[1_41,1_15,2_09,1_32],[68,1_49,1_33,1_66],[1_41,1_49,1_87,1_64],[1_95,1_48,2_87,1_65],[1_95,1_48,2_87,1_65],[1_95,1_48,2_87,1_65],[2_95,1_48,3_49,1_65],[4_41,1_49,4_92,1_66],[4_97,1_49,5_46,1_64],[64,2_01,1_25,2_18],[10_00,10_00,10_00,10_00]],[[0,0,0,0],[6_62,1_50,7_54,1_66],[6_65,1_99,7_42,2_11],[5_19,2_13,5_54,2_28],[5_19,2_13,5_54,2_28],[1_34,4_33,1_87,4_54],[1_30,4_67,2_04,4_80],[1_30,4_67,2_04,4_80],[1_30,4_67,2_04,4_80],[1_30,4_67,2_04,4_80],[1_30,4_67,2_04,4_80],[3_14,4_69,3_76,4_82],[5_04,6_84,5_82,7_06],[9_41,8_25,9_73,9_00],[9_41,8_25,9_73,9_00],[9_41,8_25,9_73,9_00],[9_41,8_25,9_73,9_00],[6_10,7_49,6_52,7_65],[1_30,6_59,1_68,6_72],[1_76,6_57,2_37,6_72],[2_38,6_57,3_12,6_72],[4_43,6_53,6_28,6_72],[4_43,6_53,6_28,6_72],[7_16,3_01,8_25,3_17],[10_00,10_00,10_00,10_00]]]							)  # noqa: E231
						lowercase							:     int									=	tf.convert_to_tensor([[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]]							)  # noqa: E231
						# these are sequence labels (i.e. at the token level)
						lowercase							:     Optional[Any]									=	tf.convert_to_tensor([[-1_00,10,10,10,9,1,-1_00,7,7,-1_00,7,7,4,2,5,2,8,8,-1_00,-1_00,5,0,3,2,-1_00],[-1_00,12,12,12,-1_00,12,10,-1_00,-1_00,-1_00,-1_00,10,12,9,-1_00,-1_00,-1_00,10,10,10,9,12,-1_00,10,-1_00]]							)  # noqa: E231
						# fmt: on

						return input_ids, attention_mask, bbox, token_type_ids, labels







@require_tf
class 				UpperCAmelCase						( unittest.TestCase       ):

					@slow
					def 							_lowerCAmelCase						(      self   :       str       ):
											lowercase							:     Any									=	TFLayoutLMModel.from_pretrained('''microsoft/layoutlm-base-uncased'''       )

											lowercase							:     List[Any]									=	prepare_layoutlm_batch_inputs()

											# forward pass
											lowercase							:     Tuple									=	model(input_ids=SCREAMING_SNAKE_CASE_			,   bbox=SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_       )

											# test the sequence output on [0, :3, :3]
											lowercase							:     Union[str, Any]									=	tf.convert_to_tensor(
											    [[0.17_85, -0.19_47, -0.04_25], [-0.32_54, -0.28_07, 0.25_53], [-0.53_91, -0.33_22, 0.33_64]]			,   )

											self.assertTrue(np.allclose(outputs.last_hidden_state[0, :3, :3]			,   SCREAMING_SNAKE_CASE_			,   atol=1E-3       )       )

											# test the pooled output on [1, :3]
											lowercase							:     Optional[Any]									=	tf.convert_to_tensor([-0.65_80, -0.02_14, 0.85_52]       )

											self.assertTrue(np.allclose(outputs.pooler_output[1, :3]			,   SCREAMING_SNAKE_CASE_			,   atol=1E-3       )       )

					@slow
					def 							_lowerCAmelCase						(      self   :       int       ):
											# initialize model with randomly initialized sequence classification head
											lowercase							:     Tuple									=	TFLayoutLMForSequenceClassification.from_pretrained('''microsoft/layoutlm-base-uncased'''			,   num_labels=2       )

											lowercase							:     List[str]									=	prepare_layoutlm_batch_inputs()

											# forward pass
											lowercase							:     Union[str, Any]									=	model(
											    input_ids=SCREAMING_SNAKE_CASE_			,   bbox=SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_			,   labels=tf.convert_to_tensor([1, 1]       )			,   )

											# test whether we get a loss as a scalar
											lowercase							:     List[Any]									=	outputs.loss
											lowercase							:     List[Any]									=	(2,)
											self.assertEqual(loss.shape			,   SCREAMING_SNAKE_CASE_       )

											# test the shape of the logits
											lowercase							:     List[Any]									=	outputs.logits
											lowercase							:     List[str]									=	(2, 2)
											self.assertEqual(logits.shape			,   SCREAMING_SNAKE_CASE_       )

					@slow
					def 							_lowerCAmelCase						(      self   :       Optional[Any]       ):
											# initialize model with randomly initialized token classification head
											lowercase							:     Dict									=	TFLayoutLMForTokenClassification.from_pretrained('''microsoft/layoutlm-base-uncased'''			,   num_labels=13       )

											lowercase							:     Union[str, Any]									=	prepare_layoutlm_batch_inputs()

											# forward pass
											lowercase							:     Optional[int]									=	model(
											    input_ids=SCREAMING_SNAKE_CASE_			,   bbox=SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_			,   labels=SCREAMING_SNAKE_CASE_       )

											# test the shape of the logits
											lowercase							:     List[str]									=	outputs.logits
											lowercase							:     Tuple									=	tf.convert_to_tensor((2, 25, 13)       )
											self.assertEqual(logits.shape			,   SCREAMING_SNAKE_CASE_       )




					@slow
					def 							_lowerCAmelCase						(      self   :       Optional[int]       ):
											# initialize model with randomly initialized token classification head
											lowercase							:     Any									=	TFLayoutLMForQuestionAnswering.from_pretrained('''microsoft/layoutlm-base-uncased'''       )

											lowercase							:     int									=	prepare_layoutlm_batch_inputs()

											# forward pass
											lowercase							:     str									=	model(input_ids=SCREAMING_SNAKE_CASE_			,   bbox=SCREAMING_SNAKE_CASE_			,   attention_mask=SCREAMING_SNAKE_CASE_			,   token_type_ids=SCREAMING_SNAKE_CASE_       )

											# test the shape of the logits
											lowercase							:     List[Any]									=	tf.convert_to_tensor((2, 25)       )
											self.assertEqual(outputs.start_logits.shape			,   SCREAMING_SNAKE_CASE_       )
											self.assertEqual(outputs.end_logits.shape			,   SCREAMING_SNAKE_CASE_       )







def  lowerCAmelCase_	(lowerCAmelCase__:		list  ):





			"""simple docstring"""


			if len(lowerCAmelCase__  ) <= 1:
						return [tuple(lowerCAmelCase__  )]

			UpperCAmelCase_:		List[Any]							      =     []

			def generate(lowerCAmelCase__:		int		,						lowerCAmelCase__:		list  ):
						if k == 1:
									res.append(tuple(arr[:]  )  )
									return

						generate(k - 1		,						lowerCAmelCase__  )

						for i in range(k - 1  ):
									if k % 2 == 0:  # k is even
												UpperCAmelCase_      ,							UpperCAmelCase_:		Union[str, Any]							      =     arr[k - 1], arr[i]
									else:  # k is odd
												UpperCAmelCase_      ,							UpperCAmelCase_:		Optional[int]							      =     arr[k - 1], arr[0]
									generate(k - 1		,						lowerCAmelCase__  )

			generate(len(lowerCAmelCase__  )		,						lowerCAmelCase__  )
			return res


if __name__ == "__main__":
	a      :  Optional[Any]			     =			input('Enter numbers separated by a comma:\n').strip()
	a      :  str			     =			[int(item) for item in user_input.split(',')]
	print(heaps(arr))






